In wireless communications, as well as in other communications systems, Turbo receiver (TRX) architectures have become popular in a variety of scenarios. The Turbo concept was originally presented in the context of Turbo codes—see C. Berrou, A. Glavieux, and P. Thitimajshima, “Near Shannon limit error-correcting coding and decoding: Turbo-codes”, Proceedings of ICC 1993, Geneva, Switzerland, pp. 1064-1070. During the recent decades, the Turbo principle has moved beyond channel coding and is being used in a myriad of iterative approaches for general receiver applications.
All TRX algorithms are based on the principle of belief propagation. A number of “decoding” stages provide soft output information about some component of the received signal that is an improved, value-added version of the input soft information. The soft decoders aggregate the local “constituent code” constraints and any new information available from other decoders in the Turbo structure.
The “constituent code” and its corresponding “decoder” may refer to the traditional channel coding blocks, but also e.g. to the multipath channel and the corresponding equalizer, or the multiple-access channel and the corresponding interference cancellation (IC) operation. Some concrete examples of Turbo structures beyond channel coding are the Turbo equalizer, such as described in C. Laot, R. Le Bidan, and D. Leroux, “Low-complexity MMSE turbo equalization: A possible solution for EDGE,” IEEE Trans. Wireless Commun., vol. 4, no. 3, pp. 965-974, May 2005. Turbo interference cancellation (Turbo-IC) with soft Turbo decoder (TDEC) for MIMO reception represents another useful example of TRX architectures, such as described in C. Park, Y.-P. E. Wang, G. Jongren, and D. Hammarwall, “Evolution of uplink MIMO for IMT-Advanced,” IEEE Commun. Magazine, vol. 49, no. 2, pp. 112-121, February 2011. Turbo-IC receivers typically employ iterative soft IC methods to treat a mix of signal components and can approach the performance of joint detection/decoding but with dramatically lower complexity.